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10.1089/cmb.2014.0221 http://scihub22266oqcxt.onion/10.1089/cmb.2014.0221 C4442588!4442588!25383910     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Comput+Biol 2015 ; 22 (3): 236-49 Nephropedia Template TP {{tp|p=25383910|t=2015. A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression |pdf=|usr=}}{{25383910}} gab.com Text A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression JO: J Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=25383910 #FOAvip Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. Twit Text FOAVip A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression ????J Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=25383910 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25383910 #FOAvip English Wikipedia <ref>{{Cite pmid|25383910}}</ref> A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression #MMPMID25383910 Nguyen N; Vo A; Choi I; Won KJ J Comput Biol 2015[Mar]; 22 (3): 236-49 PMID25383910show ga Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. äA Stationary Wavelet Entropy-Based Clustering Approach Accurately Pred(epmc).pdf DeepDyve Pubget Overpricing